What can you learn from the dashboards?

Has there been a sudden spike or drop off in API traffic? Which app developers are most successful? What is the adoption rate of your API among developers? Which API methods are most popular? The Edge Analytics dashboards are designed specifically to answer questions like these.

In the background, Apigee Edge collects information as data passes through your APIs. The dashboards provide a powerful way to use this data immediately. If you see something of interest in a graph or chart, an anomaly or sudden change, you can then drill deeper to uncover as much detail as you require. If you notice that a particular developer is experiencing a lot of errors or a sudden drop in traffic, you can contact that developer proactively. Dashboards give you insight into your APIs that allows you to take action.

What's the delay interval for receiving data?

Can I customize the dashboards?

Yes, many dashboards let you select which metrics to analyze, date ranges, data aggregation intervals, and many other variables. If the built-in dashboards do not suit your needs, you can create custom reports, which are dashboards you create by selecting the analytic dimensions and metrics that you wish to analyze. Custom reports let you "drill down" into your API's analytic data until you achieve the granularity you require.

How are the dashboards organized?

Most of the Apigee Analytics dashboards are organized and function much like the one below. If you understand how to use this dashboard, you'll be comfortable navigating the others.

Data range and aggregation settings - Let you select the of dates for which to display data and the aggregation or "granularity" of data to display.

Graph syles - All dashboards include one or more graphical charts, including line graphs, bar graphs, and pie charts.

When you select a smaller aggregation interval the larger the dataset the dashboard is working with. Performance tends to increase when you select a larger aggregation interval. For example, performance is greater if you select By Day rather than By Minute.

What are the most common features in the dashboards?

Dashboards have a set of common features, including time range and data aggregation settings, view togbgles, click and drag zooming on charts, mouse-over hover for more details on charts and other regions, and selectors for choosing the data to display in a chart. If you understand how to use one kind of dashboard, you'll be comfortable using the others.

Toggle the view - Some dashboards let you toggle between distinct views or toggle between Detail and Summary views.

Set the time range - You can select the time range over which the dashboard displays its data. Select Custom to use a calendar-style date picker to select the interval.

For Cloud-based installations, data older than six months from the current date is not accessible by default. If you want to access data older than six months, contact Apigee Support.

For Private Cloud installations, the maximum time frame for running custom reports through the UI is 15 days. To increase that to 31 days:

Add the following line to <install_root>/apigee4/conf/ui/apigee.conf:apigee.feature.enableForceRangeLimit="false"

Restart the the UI (you may have to clear your browser cache to get the new behavior):apigee4/bin/apigee-service ui restart

Note: When you select a smaller aggregation interval the larger the dataset the dashboard is working with. Performance tends to increase when you select a larger aggregation interval. For example, performance is greater if you select By Day rather than By Minute.

Zoom in - You can zoom in on chart data by clicking and dragging.

Hover mouse over graphs - You can mouse over any point on a graph for more context about the data at that point.

Hover mouse over labels - You can sometimes hover over a label for more details. Look for the "?" cursor as you mouse around.

Export data to file - Click Combined CSV to download a single CSV file that contains a combined set of data from all charts on the page. Alternatively, click CSV adjacent to a chart to download data specific to that chart only.

The following figure highlights these feature areas:

Here's another dashboard that includes additional features that you'll see in some other dashboards:

Analyzing spikes or drops in traffic (anomalies)

If you see a dramatic rise (a "spike") or a dramatic drop in the traffic, you can get further detail, by checking the Investigate Anomalies checkbox on the API Proxies page and clicking on a point in the chart that corresponds to the spike or drop.

Watch a short video to learn how the Anomaly investigation tool works.

In response, you'll be able to view the traffic pattern before, at, and after the spike or drop. You can display the Investigate Anomalies data by any of the dimensions available by default in Apigee Edge as well as by custom dimensions. This gives you enhanced insight into the cause of a spike or drop and enables you to correlate it to factors such as developer, developer app, resource, client IP address, or target URL.

Viewing moving averages and alerts

In addition to the Investigate Anomalies checkbox, there are two checkboxes displayed for the APIs on the API Proxies page or for an API on its detail page.

Show Moving Averages

Check this checkbox to view a moving average for the API. You can check this checkbox for multiple APIs to view a moving average that includes the set of these APIs. A moving average is a series of averages taken over sucessive subsets of a complete set of data. It's especially useful in viewing trends. The moving average is displayed as a band whose limits are +-20% of the calculated moving average data points.

Show Alerts

Select this checkbox (on the API Proxies page) to view the number of times that the moving average for the API exceeded the +-20% limit.

Reading dispersion box plots

When an analytics report illustrates an average, as well as minimum and maximum values, we display an accompanying dispersion box plot, as called out in the custom report below.

At a glance, a dispersion box plot enables you to see the central tendency and dispersion of your data. A dispersion box plot surfaces the five key numbers when it comes to illustrating averaged analytics data:

In this example, the area within the box indicates the most typical average target response times experienced by your traffic — 50% of your traffic, to be exact.

The line extending from the left side of the box indicates the average target response times experienced by 25% of your traffic.

The line extending from the right of the box indicates the average target response times experienced by the remaining 25% of your traffic.

The longer these lines, or “whiskers,” the more extreme your outlier values.